Potential Source Regions and Transportation Pathways of Reactive Gases at a Regional Background Site in Northwestern China

Zhao, Quanwei; He, Qing; Jin, Lili; Wang, Jianlin

doi:10.1155/2021/9933466

Cited by 5 publications

(6 citation statements)

References 103 publications

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Section: Health Risk Assessmentsupporting

confidence: 84%

“…However, the CR values of PM2.5 were all greater than 1.0 × 10 −4 , which had a high carcinogenic risk. In other countries, the same results were obtained by Othman et al [26] in Selangor, Peninsular Malaysia, and in China, similar results were obtained by Wang et al [25] in Yancheng, Jiangsu, China. In Shenyang, the site with the highest HQ mean for O3 was S8, reaching 0.0427; the site with the highest HQ mean for PM2.5 was S1, reaching 0.0675; the site with the highest CR mean for PM2.5 was S1, reaching 0.0145.…”

Section: Health Risk Assessmentsupporting

confidence: 84%

“…In the CWT analysis method, each grid point is assigned a degree of weight. By introducing the same numerical correction from W ij in the PSCF method, the weighted average concentration value (WCWT value) can be used to distinguish the source intensity of potential sources [25,26].…”

Section: Cwt Analysismentioning

confidence: 99%

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Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

Fang

Gao

et al. 2021

Atmosphere

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This study systematically investigated the pollution characteristics of atmospheric O3 and PM2.5, regional transport, and their health risks in three provincial capitals in northeast China during 2016–2020. The results show that O3 concentrations showed a trend of high summer and low winter, while PM2.5 concentrations showed a trend of high winter and low summer during these five years. The results of the correlation analysis indicate that external sources contribute more O3, while PM2.5 is more from local sources. The backward trajectory clustering analysis results showed that Changchun had the highest share of northwest trajectory with a five-year average value of 67.89%, and the city with the highest percentage of southwest trajectory was Shenyang with a five-year average value of 23.95%. The backward trajectory clustering analysis results showed that the share of the northwest trajectory decreased and the share of the southwest trajectory increased for all three cities in 2020 compared to 2016. The results of the potential source contribution function (PSCF) and concentration weighting trajectory (CWT) analysis showed that the main potential source areas and high concentration contribution areas for PM2.5 in the northeast were concentrated in Mongolia, Inner Mongolia, Shandong Province, and the northeast, and for O3 were mainly located in Shandong, Anhui, and Jiangsu Provinces, and the Yellow Sea and Bohai Sea. The non-carcinogenic risk of PM2.5 in Harbin was high with a HQ of 2.04, while the other cities were at acceptable levels (HQ < 0.69) and the non-carcinogenic risk of O3 was acceptable in all three cities (HQ < 0.22). However, PM2.5 had a high carcinogenic risk (4 × 10−4 < CR < 0.44) and further treatment is needed to reduce the risk.

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Section: Health Risk Assessmentsupporting

confidence: 84%

Section: Health Risk Assessmentsupporting

confidence: 84%

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Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

Fang

Gao

et al. 2021

Atmosphere

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“…Most of the air masses arriving at Akedala station passed through eastern Kazakhstan; therefore, the CO 2 and CO at Akedala station were mainly from eastern Kazakhstan in summer. However, in contrast to other seasons, the strong convection and better diffusion conditions in summer could lead to the reduction of CO 2 and CO concentrations during long-distance transport [ 44 ].…”

Section: Resultsmentioning

confidence: 99%

Analysis of Atmospheric CO2 and CO at Akedala Atmospheric Background Observation Station, a Regional Station in Northwestern China

Zhao

et al. 2022

IJERPH

Self Cite

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Air samples were collected by flasks and analyzed via a Picarro G2401 gas analyzer for carbon dioxide (CO2) and carbon monoxide (CO) at the Akedala Atmospheric Background Station in Xinjiang, China, from September 2009 to December 2019, to analyze the changes in the characteristics of atmospheric CO2 and CO and determine the sources. The results show that the annual average CO2 concentration showed an increasing trend (growth rate: 1.90 ppm year−1), ranging from 389.80 to 410.43 ppm, and the annual average CO concentration also showed an increasing trend (growth rate: 1.78 ppb year−1), ranging from 136.30 to 189.82 ppb. The CO2 concentration and growth rate were the highest in winter, followed by autumn, spring, and summer. The CO concentration and growth rate were also the highest in winter due to anthropogenic emissions, ecosystem effects, and diffusion conditions. The main trajectories of CO2 and CO determined by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were parallel to the Irtysh River valley and then passed through the Old Wind Pass. Furthermore, the main source regions of CO2 and CO at the Akedala Station were eastern Kazakhstan, southern Russia, western Mongolia, and the Xinjiang Tianshan North Slope Economic Zone of China. This study reflects the characteristics of long-term changes in CO2 and CO concentrations at the Akedala station and provides fundamental data for the studies on environmental changes and climate change in Central Asia.

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“…The CWT analysis method can obtain the difference in the pollution level of contaminated trajectories by calculating the weighted degree. In the CWT analysis method, each grid point is assigned a degree of weight [ 36 ]. By introducing the same numerical correction from W ij in the PSCF method, the weighted average concentration value (WCWT value) can be used to distinguish the source intensity of potential sources.…”

Section: Methodsmentioning

confidence: 99%

Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016–2020

Fang

Wang

et al. 2021

IJERPH

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Northeast China is an essential industrial development base in China and the regional air quality is severely affected by PM2.5 pollution. In this paper, spatial autocorrelation, trajectory clustering, hotspot analysis, PSCF and CWT analysis are used to explore the spatial pollution characteristics of PM2.5 and determine the atmospheric regional transmission pattern for 40 cities in Northeast China from 2016 to 2020. Analysis of PM2.5 concentration characteristics in the northeast indicates that the annual average value and total exceedance days of PM2.5 concentration in Northeast China showed a U-shaped change, with the lowest annual average PM2.5 concentration (31 μg/m3) in 2018, decreasing by 12.1% year-on-year, and the hourly PM2.5 concentration exploding during the epidemic lockdown period in 2020. A stable PM2.5 pollution band emerges spatially from the southwest to Northeast China. Spatially, the PM2.5 in Northeast China has a high degree of autocorrelation and a south-hot–north-cool characteristic, with all hotspots concentrated in the most polluted Liaoning province, which exhibits the H–H cluster pattern and hotspot per year. Analysis of the air mass trajectories, potential source contributions and concentration weight trajectories in Northeast China indicates that more than 74% of the air mass trajectories were transmitted to each other between the three heavily polluted cities, with the highest mean value of PM2.5 pollution trajectories reaching 222.4 μg/m3, and the contribution of daily average PM2.5 concentrations exceeding 60 μg/m3 within Northeast China. Pollution of PM2.5 throughout the Northeast is mainly influenced by short-range intra-regional transport, with long-range transport between regions also being an essential factor; organized integration is the only fundamental solution to air pollution.

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Potential Source Regions and Transportation Pathways of Reactive Gases at a Regional Background Site in Northwestern China

Cited by 5 publications

References 103 publications

Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

Analysis of Atmospheric CO2 and CO at Akedala Atmospheric Background Observation Station, a Regional Station in Northwestern China

Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016–2020

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